Implement Gemini LLM module for document generation (first non tested prototype)

services/modules/llm-gemini/gemini.js

@@ -0,0 +1,55 @@
+import fs from "fs";
+import { dirname } from "path";
+import { fileURLToPath } from "url";
+
+const __dirname = dirname(fileURLToPath(import.meta.url));
+const { GoogleGenAI } = require("@google/genai");
+
+const ai = new GoogleGenAI({
+    apiKey: process.env.GOOGLE_API_KEY
+});
+
+const outputDir = `${__dirname}/../../../storage/documents`;
+if (!fs.existsSync(outputDir)) {
+    fs.mkdirSync(outputDir, { recursive: true });
+}
+
+module.exports = {
+    name: "llm-gemini",
+    type: "llm",
+    displayname: "Gemini LLM",
+
+    async function(parameter) {
+        try {
+            console.log("Gemini LLM module invoked with parameters:", parameter);
+
+            await this.createDocumentFromTranscript(
+                parameter.inputTranscriptPath,
+                parameter.documentType
+            );
+
+        } catch (error) {
+            console.error("Error in Gemini LLM module:", error);
+        }
+    },
+
+    createDocumentFromTranscript: async function(transcriptPath, documentType) {
+        try {
+            const transcript = await fs.promises.readFile(transcriptPath, "utf-8");
+
+            const text = `${documentType}\n\n${transcript}`;
+
+            const response = await ai.models.generateContent({
+                model: "gemini-2.5-flash",
+                contents: text
+            });
+
+            const output = response.text ?? "";
+
+            fs.writeFileSync(`${outputDir}/test.md`, output, "utf8");
+            console.log("Generated document written to test.md");
+        } catch (error) {
+            console.error("Error generating content:", error);
+        }
+    }
+};